library(here)
library(plotly)
theme_set(theme_minimal())
source(here("02_scripts/01_fun_data.R"))
t_owsa_ini_pop <- read.csv(file = here("01_data/ows_tbl_ini_pop.csv")) %>% select(-X)
ows_tbl_prob <- read.csv(, file = here("01_data/ows_tbl_prob.csv")) %>% select(-X)t_owsa_ini_pop_costs <- t_owsa_ini_pop %>%
select(costs_low, costs_high, name)
t_owsa_ini_pop_costs$name <- reorder(t_owsa_ini_pop_costs$name, t_owsa_ini_pop$costs_range)
t_owsa_ini_pop_costs <- t_owsa_ini_pop_costs %>%
pivot_longer(1:2, names_to = "group", values_to = "costs") %>%
mutate(costs_new = (costs - mod_basecase$total_net_present_cost)) %>%
filter(costs_new != 0) %>%
mutate(group = ifelse(group == "costs_high", "+25%",
ifelse(group == "costs_low", "-25%", group)))
ggplotly(ggplot() +
geom_bar(data = t_owsa_ini_pop_costs %>% filter(abs(costs_new) >= 500000000),
aes(x = name, y = costs_new, fill = group, color = group), stat = "identity") + coord_flip() +
ylab("Difference in Costs from the basecase value") + xlab("") +
labs(color = "Difference in initial \n population value", fill = "Difference in initial \n population value") +
scale_x_discrete(labels=c("ini_pop_BN_CHRONIC" = "Chronic pain, no use",
"ini_pop_BN_PN" = "Pain free, no use",
"ini_pop_BN_ACUTE" = "Acute pain, no use",
"ini_pop_BN_CANCER" = "Cancer, no use",
"ini_pop_BN_OTHER" = "Other, no use",
"ini_pop_BPO_ACUTE" = "Acute pain, Rx use",
"ini_pop_BPO_CHRONIC" = "Chronic pain, Rx use",
"ini_pop_BPO_CANCER" = "Cancer, Rx use",
"ini_pop_BPO_OTHER" = "Other, Rx use",
"ini_pop_BPO_MISUSE" = "Rx opioid misuse",
"ini_pop_BI_ILLICIT" = "Illicit opioid use")) +
scale_color_brewer(palette = "Dark2") +
scale_fill_brewer(palette = "Dark2"))t_owsa_ini_pop_deaths <- t_owsa_ini_pop %>%
select(deaths_low, deaths_high, name)
t_owsa_ini_pop_deaths$name <- reorder(t_owsa_ini_pop_deaths$name, t_owsa_ini_pop$deaths_range)
t_owsa_ini_pop_deaths <- t_owsa_ini_pop_deaths %>%
pivot_longer(1:2, names_to = "group", values_to = "deaths") %>%
mutate(deaths_new = (deaths - mod_basecase$m_M[181, "BO_DEATH"])) %>%
filter(deaths_new != 0) %>%
mutate(group = ifelse(group == "deaths_high", "+25%",
ifelse(group == "deaths_low", "-25%", group)))
ggplotly(ggplot() +
geom_bar(data = t_owsa_ini_pop_deaths %>% filter(abs(deaths_new) >= 5000),
aes(x = name, y = deaths_new, fill = group, color = group), stat = "identity") + coord_flip() +
ylab("Difference in Deaths from the basecase value") + xlab("") +
labs(color = "Difference in initial \n population value", fill = "Difference in initial \n population value") +
scale_x_discrete(labels=c("ini_pop_BN_CHRONIC" = "Chronic pain, no use",
"ini_pop_BN_PN" = "Pain free, no use",
"ini_pop_BN_ACUTE" = "Acute pain, no use",
"ini_pop_BN_CANCER" = "Cancer, no use",
"ini_pop_BN_OTHER" = "Other, no use",
"ini_pop_BPO_ACUTE" = "Acute pain, Rx use",
"ini_pop_BPO_CHRONIC" = "Chronic pain, Rx use",
"ini_pop_BPO_CANCER" = "Cancer, Rx use",
"ini_pop_BPO_OTHER" = "Other, Rx use",
"ini_pop_BPO_MISUSE" = "Rx opioid misuse",
"ini_pop_BI_ILLICIT" = "Illicit opioid use",
"ini_pop_BPO_PALLIATIVE" = "Palliative, Rx use")) +
scale_color_brewer(palette = "Dark2") +
scale_fill_brewer(palette = "Dark2"))t_owsa_ini_pop_oddeaths <- t_owsa_ini_pop %>%
select(od_deaths_low, od_deaths_high, name)
t_owsa_ini_pop_oddeaths$name <- reorder(t_owsa_ini_pop_oddeaths$name, t_owsa_ini_pop$od_deaths_range)
t_owsa_ini_pop_oddeaths <- t_owsa_ini_pop_oddeaths %>%
pivot_longer(1:2, names_to = "group", values_to = "oddeaths") %>%
mutate(oddeaths_new = (oddeaths - (mod_basecase$m_M[181, "BO_OD_DEATH"] + mod_basecase$extra_od_deaths))) %>%
filter(oddeaths_new != 0) %>%
mutate(group = ifelse(group == "od_deaths_high", "+25%",
ifelse(group == "od_deaths_low", "-25%", group)))
ggplotly(ggplot() +
geom_bar(data = t_owsa_ini_pop_oddeaths %>% filter(abs(oddeaths_new) >= 100),
aes(x = name, y = oddeaths_new, fill = group, color = group), stat = "identity") + coord_flip() +
ylab("Difference in opioid-related overdose deaths from the basecase value") + xlab("") +
labs(color = "Difference in initial \n population value", fill = "Difference in initial \n population value") +
scale_x_discrete(labels=c("ini_pop_BN_CHRONIC" = "Chronic pain, no use",
"ini_pop_BN_PN" = "Pain free, no use",
"ini_pop_BN_ACUTE" = "Acute pain, no use",
"ini_pop_BN_CANCER" = "Cancer, no use",
"ini_pop_BN_OTHER" = "Other, no use",
"ini_pop_BPO_ACUTE" = "Acute pain, Rx use",
"ini_pop_BPO_CHRONIC" = "Chronic pain, Rx use",
"ini_pop_BPO_CANCER" = "Cancer, Rx use",
"ini_pop_BPO_OTHER" = "Other, Rx use",
"ini_pop_BPO_MISUSE" = "Rx opioid misuse",
"ini_pop_BI_ILLICIT" = "Illicit opioid use",
"ini_pop_BPO_PALLIATIVE" = "Palliative, Rx use",
"ini_pop_BS_OAT_MAINT" = "OAT maintenance")) +
scale_color_brewer(palette = "Dark2") +
scale_fill_brewer(palette = "Dark2"))ows_tbl_prob_costs <- ows_tbl_prob %>%
select(costs_low, costs_high, name, group) %>%
mutate(name = paste(name, group, sep = "_")) %>%
rename(grp = group)
ows_tbl_prob_costs$name <- reorder(ows_tbl_prob_costs$name, ows_tbl_prob$cost_range)
ows_tbl_prob_costs <- ows_tbl_prob_costs %>%
pivot_longer(1:2, names_to = "group", values_to = "costs") %>%
mutate(costs_new = (costs - as.numeric(mod_basecase$total_net_present_cost)),
costs_new_per = (costs_new/as.numeric(mod_basecase$total_net_present_cost)) * 100) %>%
filter(costs_new != 0) %>%
mutate(group = ifelse(group == "costs_high", "+25%",
ifelse(group == "costs_low", "-25%", group)))
name_cost_1 <- ows_tbl_prob_costs %>% filter(abs(costs_new_per) >= 0.5) %>% select(name)
name_cost_2 <- ows_tbl_prob_costs %>% filter(abs(costs_new_per) >= 1.5) %>% select(name)
ggplotly(ggplot() +
geom_bar(data = ows_tbl_prob_costs %>% filter(name %in% name_cost_1$name),
aes(x = name, y = costs_new, fill = group, color = group), stat = "identity") + coord_flip() +
ylab("Difference in Costs from the basecase value") + xlab("") +
labs(color = "Difference in transition \n probability value", fill = "Difference in transition \n probability value") +
scale_x_discrete(labels=c("p_BN_ACUTE_BN_PN" = "Pain free, no use to acute pain, no use",
"p_BN_CANCER_BN_PN" = "Pain free, no use to cancer, no use",
"p_BPO_ACUTE_BN_PN" = "Pain free, no use to acute pain, Rx use",
"p_BPO_MISUSE_BN_PN" = "Pain free, no use to Rx opioid misuse",
"p_BN_CHRONIC_BN_ACUTE" = "Acute pain, no use to chronic pain, no use",
"p_BN_CANCER_BN_CHRONIC" = "Chronic pain, no use to cancer, no use",
"p_BPO_MISUSE_BN_CHRONIC" = "Chronic pain, no use to Rx opioid misuse",
"p_BPO_OTHER_BN_OTHER" = "Other, no use to other, Rx use",
"p_BN_CHRONIC_BPO_ACUTE" = "Acute pain, Rx use to chronic pain, no use",
"p_BPO_MISUSE_BPO_CHRONIC" = "Chronic pain, Rx use to Rx opioid misuse",
"p_BO_OD_RX_BPO_CHRONIC" = "Chronic pain, Rx use to Rx opioid overdose",
"p_BO_DEATH_BPO_CANCER" = "Cancer, Rx use to death",
"p_BN_OTHER_BPO_OTHER" = "Other, Rx use to other, no use",
"p_BPO_MISUSE_BPO_OTHER" = "Other, Rx use to Rx opioid misuse",
"p_BN_PN_BPO_MISUSE" = "Rx opioid misuse to pain free, no use",
"p_BI_ILLICIT_BPO_MISUSE" = "Rx opioid misuse to illicit opioid use",
"p_BS_DETOX_BI_ILLICIT" = "Illicit opioid use to detox/withdrawal man.",
"p_BS_OAT_INI_BS_DETOX" = "Detox/withdrawal man. to OAT initiation",
"p_BS_OAT_MAINT_BS_OAT_INI" = "OAT initiation to OAT maintenance",
"p_BS_OAT_MAINT_BS_OAT_MAINT" = "OAT maintenance stay",
"p_BO_OD_DEATH_BO_OD_RX" = "Rx opioid overdose to death",
"p_BN_PALLIATIVE_BN_PN" = "Pain Free, no use, to Palliative, no use",
"p_BO_DEATH_BN_PN" = "Pain Free, no use, to Death",
"p_BN_PALLIATIVE_BN_CHRONIC" = "Chronic pain, no use to palliative, no use",
"p_BPO_CHRONIC_BN_CHRONIC" = "Chronic pain, no use to chronic pain, Rx use",
"p_BO_DEATH_BN_CHRONIC" = "Chronic pain, no use to death",
"p_BO_DEATH_BN_OTHER" = "Other no use to death",
"p_BN_CHRONIC_BPO_CHRONIC" = "Chronic pain, Rx use to chronic pain, no use",
"p_BO_DEATH_BPO_CHRONIC" = "Chronic pain, Rx use to death",
"p_BPO_MISUSE_BPO_CANCER" = "Cancer, Rx use to Rx opioid misuse",
"p_BO_OD_RX_BPO_CANCER" = "Cancer, Rx use to Rx opioid overdose",
"p_BO_DEATH_BPO_MISUSE" = "Rx opioid misuse to death",
"p_BR_OAT_MAINT_BR_OAT_MAINT" = "R: OAT maintenance stay")) +
scale_color_brewer(palette = "Dark2") +
scale_fill_brewer(palette = "Dark2"))ggplotly(ggplot() +
geom_bar(data = ows_tbl_prob_costs %>% filter(name %in% name_cost_2$name),
aes(x = name, y = costs_new, fill = group, color = group), stat = "identity") + coord_flip() +
ylab("Difference in Costs from the basecase value") + xlab("") +
labs(color = "Difference in transition \n probability value", fill = "Difference in transition \n probability value") +
scale_x_discrete(labels=c("p_BN_ACUTE_BN_PN" = "Pain free, no use to acute pain, no use",
"p_BN_CANCER_BN_PN" = "Pain free, no use to cancer, no use",
"p_BPO_ACUTE_BN_PN" = "Pain free, no use to acute pain, Rx use",
"p_BPO_MISUSE_BN_PN" = "Pain free, no use to Rx opioid misuse",
"p_BN_CHRONIC_BN_ACUTE" = "Acute pain, no use to chronic pain, no use",
"p_BN_CANCER_BN_CHRONIC" = "Chronic pain, no use to cancer, no use",
"p_BPO_MISUSE_BN_CHRONIC" = "Chronic pain, no use to Rx opioid misuse",
"p_BPO_OTHER_BN_OTHER" = "Other, no use to other, Rx use",
"p_BN_CHRONIC_BPO_ACUTE" = "Acute pain, Rx use to chronic pain, no use",
"p_BPO_MISUSE_BPO_CHRONIC" = "Chronic pain, Rx use to Rx opioid misuse",
"p_BO_OD_RX_BPO_CHRONIC" = "Chronic pain, Rx use to Rx opioid overdose",
"p_BO_DEATH_BPO_CANCER" = "Cancer, Rx use to death",
"p_BN_OTHER_BPO_OTHER" = "Other, Rx use to other, no use",
"p_BPO_MISUSE_BPO_OTHER" = "Other, Rx use to Rx opioid misuse",
"p_BN_PN_BPO_MISUSE" = "Rx opioid misuse to pain free, no use",
"p_BI_ILLICIT_BPO_MISUSE" = "Rx opioid misuse to illicit opioid use",
"p_BS_DETOX_BI_ILLICIT" = "Illicit opioid use to detox/withdrawal man.",
"p_BS_OAT_INI_BS_DETOX" = "Detox/withdrawal man. to OAT initiation",
"p_BS_OAT_MAINT_BS_OAT_INI" = "OAT initiation to OAT maintenance",
"p_BS_OAT_MAINT_BS_OAT_MAINT" = "OAT maintenance stay",
"p_BO_OD_DEATH_BO_OD_RX" = "Rx opioid overdose to death",
"p_BN_PALLIATIVE_BN_PN" = "Pain Free, no use, to Palliative, no use",
"p_BO_DEATH_BN_PN" = "Pain Free, no use, to Death",
"p_BN_PALLIATIVE_BN_CHRONIC" = "Chronic pain, no use to palliative, no use",
"p_BPO_CHRONIC_BN_CHRONIC" = "Chronic pain, no use to chronic pain, Rx use",
"p_BO_DEATH_BN_CHRONIC" = "Chronic pain, no use to death",
"p_BO_DEATH_BN_OTHER" = "Other no use to death",
"p_BN_CHRONIC_BPO_CHRONIC" = "Chronic pain, Rx use to chronic pain, no use",
"p_BO_DEATH_BPO_CHRONIC" = "Chronic pain, Rx use to death",
"p_BPO_MISUSE_BPO_CANCER" = "Cancer, Rx use to Rx opioid misuse",
"p_BO_OD_RX_BPO_CANCER" = "Cancer, Rx use to Rx opioid overdose",
"p_BO_DEATH_BPO_MISUSE" = "Rx opioid misuse to death",
"p_BR_OAT_MAINT_BR_OAT_MAINT" = "R: OAT maintenance stay")) +
scale_color_brewer(palette = "Dark2") +
scale_fill_brewer(palette = "Dark2"))ows_tbl_prob_deaths <- ows_tbl_prob %>%
select(deaths_low, deaths_high, name, group) %>%
mutate(name = paste(name, group, sep = "_")) %>%
rename(grp = group)
ows_tbl_prob_deaths$name <- reorder(ows_tbl_prob_deaths$name, ows_tbl_prob$deaths_range)
ows_tbl_prob_deaths <- ows_tbl_prob_deaths %>%
pivot_longer(1:2, names_to = "group", values_to = "deaths") %>%
mutate(deaths_new = (deaths - as.numeric(mod_basecase$m_M[181, "BO_DEATH"])),
deaths_new_per = (deaths_new/as.numeric(mod_basecase$m_M[181, "BO_DEATH"])) * 100) %>%
filter(deaths_new != 0) %>%
mutate(group = ifelse(group == "deaths_high", "+25%",
ifelse(group == "deaths_low", "-25%", group)))
name_death_1 <- ows_tbl_prob_deaths %>% filter(abs(deaths_new_per) >= 0.5) %>% select(name)
ggplotly(ggplot() +
geom_bar(data = ows_tbl_prob_deaths %>% filter(name %in% name_death_1$name),
aes(x = name, y = deaths_new, fill = group, color = group), stat = "identity") + coord_flip() +
ylab("Difference in deaths from the basecase value") + xlab("") +
labs(color = "Difference in transition \n probability value", fill = "Difference in transition \n probability value") +
scale_x_discrete(labels=c("p_BN_ACUTE_BN_PN" = "Pain free, no use to acute pain, no use",
"p_BN_CANCER_BN_PN" = "Pain free, no use to cancer, no use",
"p_BPO_ACUTE_BN_PN" = "Pain free, no use to acute pain, Rx use",
"p_BPO_MISUSE_BN_PN" = "Pain free, no use to Rx opioid misuse",
"p_BN_CHRONIC_BN_ACUTE" = "Acute pain, no use to chronic pain, no use",
"p_BN_CANCER_BN_CHRONIC" = "Chronic pain, no use to cancer, no use",
"p_BPO_MISUSE_BN_CHRONIC" = "Chronic pain, no use to Rx opioid misuse",
"p_BPO_OTHER_BN_OTHER" = "Other, no use to other, Rx use",
"p_BN_CHRONIC_BPO_ACUTE" = "Acute pain, Rx use to chronic pain, no use",
"p_BPO_MISUSE_BPO_CHRONIC" = "Chronic pain, Rx use to Rx opioid misuse",
"p_BO_OD_RX_BPO_CHRONIC" = "Chronic pain, Rx use to Rx opioid overdose",
"p_BO_DEATH_BPO_CANCER" = "Cancer, Rx use to death",
"p_BN_OTHER_BPO_OTHER" = "Other, Rx use to other, no use",
"p_BPO_MISUSE_BPO_OTHER" = "Other, Rx use to Rx opioid misuse",
"p_BN_PN_BPO_MISUSE" = "Rx opioid misuse to pain free, no use",
"p_BI_ILLICIT_BPO_MISUSE" = "Rx opioid misuse to illicit opioid use",
"p_BS_DETOX_BI_ILLICIT" = "Illicit opioid use to detox/withdrawal man.",
"p_BS_OAT_INI_BS_DETOX" = "Detox/withdrawal man. to OAT initiation",
"p_BS_OAT_MAINT_BS_OAT_INI" = "OAT initiation to OAT maintenance",
"p_BS_OAT_MAINT_BS_OAT_MAINT" = "OAT maintenance stay",
"p_BO_OD_DEATH_BO_OD_RX" = "Rx opioid overdose to death",
"p_BN_PALLIATIVE_BN_PN" = "Pain Free, no use, to Palliative, no use",
"p_BO_DEATH_BN_PN" = "Pain Free, no use, to Death",
"p_BN_PALLIATIVE_BN_CHRONIC" = "Chronic pain, no use to palliative, no use",
"p_BPO_CHRONIC_BN_CHRONIC" = "Chronic pain, no use to chronic pain, Rx use",
"p_BO_DEATH_BN_CHRONIC" = "Chronic pain, no use to death",
"p_BO_DEATH_BN_OTHER" = "Other no use to death",
"p_BN_CHRONIC_BPO_CHRONIC" = "Chronic pain, Rx use to chronic pain, no use",
"p_BO_DEATH_BPO_CHRONIC" = "Chronic pain, Rx use to death",
"p_BPO_MISUSE_BPO_CANCER" = "Cancer, Rx use to Rx opioid misuse",
"p_BO_OD_RX_BPO_CANCER" = "Cancer, Rx use to Rx opioid overdose",
"p_BO_DEATH_BPO_MISUSE" = "Rx opioid misuse to death",
"p_BR_OAT_MAINT_BR_OAT_MAINT" = "R: OAT maintenance stay")) +
scale_color_brewer(palette = "Dark2") +
scale_fill_brewer(palette = "Dark2"))oddeaths_bc <- as.numeric(mod_basecase$m_M[181, "BO_OD_DEATH"] + mod_basecase$extra_od_deaths)
ows_tbl_prob_oddeaths <- ows_tbl_prob %>%
select(od_deaths_low, od_deaths_high, name, group) %>%
mutate(name = paste(name, group, sep = "_")) %>%
rename(grp = group)
ows_tbl_prob_oddeaths$name <- reorder(ows_tbl_prob_oddeaths$name, ows_tbl_prob$od_deaths_range)
ows_tbl_prob_oddeaths <- ows_tbl_prob_oddeaths %>%
pivot_longer(1:2, names_to = "group", values_to = "oddeaths") %>%
mutate(oddeaths_new = (oddeaths - oddeaths_bc),
oddeaths_new_per = (oddeaths_new/oddeaths_bc) * 100) %>%
filter(oddeaths_new != 0) %>%
mutate(group = ifelse(group == "od_deaths_high", "+25%",
ifelse(group == "od_deaths_low", "-25%", group)))
name_oddeath_1 <- ows_tbl_prob_oddeaths %>% filter(abs(oddeaths_new_per) >= 5) %>% select(name)
ggplotly(ggplot() +
geom_bar(data = ows_tbl_prob_oddeaths %>% filter(name %in% name_oddeath_1$name),
aes(x = name, y = oddeaths_new, fill = group, color = group), stat = "identity") + coord_flip() +
ylab("Difference in opioid-related overdose death from the basecase value") + xlab("") +
labs(color = "Difference in transition \n probability value", fill = "Difference in transition \n probability value") +
scale_x_discrete(labels=c("p_BN_ACUTE_BN_PN" = "Pain free, no use to acute pain, no use",
"p_BN_CANCER_BN_PN" = "Pain free, no use to cancer, no use",
"p_BPO_ACUTE_BN_PN" = "Pain free, no use to acute pain, Rx use",
"p_BPO_MISUSE_BN_PN" = "Pain free, no use to Rx opioid misuse",
"p_BN_CHRONIC_BN_ACUTE" = "Acute pain, no use to chronic pain, no use",
"p_BN_CANCER_BN_CHRONIC" = "Chronic pain, no use to cancer, no use",
"p_BPO_MISUSE_BN_CHRONIC" = "Chronic pain, no use to Rx opioid misuse",
"p_BPO_OTHER_BN_OTHER" = "Other, no use to other, Rx use",
"p_BN_CHRONIC_BPO_ACUTE" = "Acute pain, Rx use to chronic pain, no use",
"p_BPO_MISUSE_BPO_CHRONIC" = "Chronic pain, Rx use to Rx opioid misuse",
"p_BO_OD_RX_BPO_CHRONIC" = "Chronic pain, Rx use to Rx opioid overdose",
"p_BO_DEATH_BPO_CANCER" = "Cancer, Rx use to death",
"p_BN_OTHER_BPO_OTHER" = "Other, Rx use to other, no use",
"p_BPO_MISUSE_BPO_OTHER" = "Other, Rx use to Rx opioid misuse",
"p_BN_PN_BPO_MISUSE" = "Rx opioid misuse to pain free, no use",
"p_BI_ILLICIT_BPO_MISUSE" = "Rx opioid misuse to illicit opioid use",
"p_BS_DETOX_BI_ILLICIT" = "Illicit opioid use to detox/withdrawal man.",
"p_BS_OAT_INI_BS_DETOX" = "Detox/withdrawal man. to OAT initiation",
"p_BS_OAT_MAINT_BS_OAT_INI" = "OAT initiation to OAT maintenance",
"p_BS_OAT_MAINT_BS_OAT_MAINT" = "OAT maintenance stay",
"p_BO_OD_DEATH_BO_OD_RX" = "Rx opioid overdose to death",
"p_BN_PALLIATIVE_BN_PN" = "Pain Free, no use, to Palliative, no use",
"p_BO_DEATH_BN_PN" = "Pain Free, no use, to Death",
"p_BN_PALLIATIVE_BN_CHRONIC" = "Chronic pain, no use to palliative, no use",
"p_BPO_CHRONIC_BN_CHRONIC" = "Chronic pain, no use to chronic pain, Rx use",
"p_BO_DEATH_BN_CHRONIC" = "Chronic pain, no use to death",
"p_BO_DEATH_BN_OTHER" = "Other no use to death",
"p_BN_CHRONIC_BPO_CHRONIC" = "Chronic pain, Rx use to chronic pain, no use",
"p_BO_DEATH_BPO_CHRONIC" = "Chronic pain, Rx use to death",
"p_BPO_MISUSE_BPO_CANCER" = "Cancer, Rx use to Rx opioid misuse",
"p_BO_OD_RX_BPO_CANCER" = "Cancer, Rx use to Rx opioid overdose",
"p_BO_DEATH_BPO_MISUSE" = "Rx opioid misuse to death",
"p_BR_OAT_MAINT_BR_OAT_MAINT" = "R: OAT maintenance stay",
"p_BO_OD_DEATH_BO_OD_ILLICIT" = "Illicit opioid overdose to death",
"p_BO_OD_ILLICIT_BI_ILLICIT" = "Illicit opioid use to Illicit opioid overdose",
"p_BO_OD_RX_BPO_MISUSE" = "Rx opioid misuse to Rx opioid overdose",
"p_BR_OD_ILLICIT_BR_ILLICIT" = "R: illicit opioid use to R: illicit opioid overdose",
"p_BO_OD_DEATH_BR_OD_ILLICIT" = "R: Illicit opioid overdose to death",
"p_BO_OD_ILLICIT_BS_DETOX" = "Detox/withdrawal man. to Illicit opioid overdose",
"p_BI_ILLICIT_BS_DETOX" = "Detox/withdrawal man. to illicit opioid use")) +
scale_color_brewer(palette = "Dark2") +
scale_fill_brewer(palette = "Dark2"))